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Ruslan Dautkhanov updated KYLIN-3138: ------------------------------------- Description: We just started using Kylin and quite like it so far. Although some of the datasets we have are quite wide to even consider for OLAP cubing. Unless those cuboids will be built on-demand. I know some commercial non-open source products do this successfully. This idea is to build a cuboid only when a user actually needs it. So for example, our BI dashboards does a certain rollup, so then a SQL query hits Kylin backend. Kylin realizes it hasn't built that particular cuboid just yet, so immediately starts building it. Users has to wait a bit longer first time it request that combination of dimensions. But all other requests or requests of other users will be fast from that point on. Kylin (or any other OLAP solution) wouldn't be feasible to use on very wide datasets unless this on-demand functionality is implemented. For example, some datasets we have have 100-200 dimensions. And we don't know up front rollups users would want to do. Suggesting to have a new dimension build rule "lazy / on-demand". All previous rules apply. This new rule type would mean, a cuboid for a particular set of dimensions wouldn't be built up-front if it's marked as "lazy / on-demand". Thoughts / ideas? was: We just started using Kylin and quite like it so far. Although some of the datasets we have a quite like to even consider for OLAP cubing. Unless those cuboids will be built on-demand. I know some commercial non-open source products do this successfully. This idea is to build a cuboid only when a user actually needs it. So for example, our BI dashboards does a certain rollup, so then a SQL query hits Kylin backend. Kylin realizes it hasn't built that particular cuboid just yet, so immediately starts building it. Users has to wait a bit longer first time it request that combination of dimensions. But all other requests or requests of other users will be fast from that point on. Kylin (or any other OLAP solution) wouldn't be feasible to use on very wide datasets unless this on-demand functionality is implemented. For example, some datasets we have have 100-200 dimensions. And we don't know up front rollups users would want to do. Suggesting to have a new dimension build rule "lazy / on-demand". All previous rules apply. This new rule type would mean, a cuboid for a particular set of dimensions wouldn't be built up-front if it's marked as "lazy / on-demand". Thoughts / ideas? > cuboids on-demand build > ----------------------- > > Key: KYLIN-3138 > URL: https://issues.apache.org/jira/browse/KYLIN-3138 > Project: Kylin > Issue Type: New Feature > Components: General, Job Engine, Query Engine, Spark Engine > Affects Versions: v2.2.0 > Reporter: Ruslan Dautkhanov > Assignee: Shaofeng SHI > Priority: Critical > > We just started using Kylin and quite like it so far. > Although some of the datasets we have are quite wide to even consider for > OLAP cubing. > Unless those cuboids will be built on-demand. > I know some commercial non-open source products do this successfully. > This idea is to build a cuboid only when a user actually needs it. > So for example, our BI dashboards does a certain rollup, so then a SQL > query hits Kylin backend. Kylin realizes it hasn't built that particular > cuboid just yet, > so immediately starts building it. Users has to wait a bit longer first time > it request that combination of dimensions. But all other requests or requests > of other users will be fast from that point on. > Kylin (or any other OLAP solution) wouldn't be feasible to use on very wide > datasets > unless this on-demand functionality is implemented. For example, some > datasets we have have 100-200 dimensions. And we don't know up front rollups > users would want to do. > Suggesting to have a new dimension build rule "lazy / on-demand". All > previous rules apply. This new rule type would mean, a cuboid for a > particular set of dimensions wouldn't be built up-front if it's marked as > "lazy / on-demand". > Thoughts / ideas? -- This message was sent by Atlassian JIRA (v6.4.14#64029)